gam
GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations
Science Score: 36.0%
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Repository
GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations
Basic Info
Statistics
- Stars: 34
- Watchers: 11
- Forks: 25
- Open Issues: 14
- Releases: 4
Topics
Metadata Files
README.md
GAM (Global Attribution Mapping)
Global Explanations for Deep Neural Networks
GAM explains the landscape of model predictions across subpopulations. This implementation is based on "Global Explanations for Neural Networks: Mapping the Landscape of Predictions" (AAAI/ACM AIES 2019). GAM is a method for clustering any set of local attributions - it is agnostic to the choice of model architecture and XAI method.
Installation
sh
python3 -m pip install gam
Get Started
First generate local attributions using your favorite technique, then:
```Python
from gam.gam import GAM
for a quick example use
attributions_path="tests/test_attributes.csv"Input/Output: csv (columns: features, rows: local/global attribution)
gam = GAM(attributionspath="<pathtoyourattributes>.csv", distance="spearman", k=2) gam.generate() gam.explanations [[('height', .6), ('weight', .3), ('hair color', .1)], [('weight', .9), ('weight', .05), ('hair color', .05)]]
gam.subpopulation_sizes [90, 10]
gam.subpopulations
global explanation assignment
[0, 1, 0, 0,...]
gam.plot()
bar chart of feature importance with subpopulation size
```
Tests
To run tests:
bash
$ python -m pytest tests/
Contributors
We welcome Your interest in Capital One’s Open Source Projects (the “Project”). Any Contributor to the Project must accept and sign an Agreement indicating agreement to the license terms below. Except for the license granted in this Agreement to Capital One and to recipients of software distributed by Capital One, You reserve all right, title, and interest in and to Your Contributions; this Agreement does not impact Your rights to use Your own Contributions for any other purpose.
Code of Conduct
This project adheres to the Open Code of Conduct By participating, you are expected to honor this code.
Owner
- Name: Capital One
- Login: capitalone
- Kind: organization
- Email: opensource@capitalone.com
- Location: McLean, VA
- Website: https://www.capitalone.com/tech/open-source/
- Repositories: 41
- Profile: https://github.com/capitalone
We’re an open source-first organization — actively using, contributing to and managing open source software projects.
GitHub Events
Total
- Issues event: 5
- Delete event: 2
- Push event: 2
- Pull request review event: 2
- Pull request event: 3
- Fork event: 1
- Create event: 3
Last Year
- Issues event: 5
- Delete event: 2
- Push event: 2
- Pull request review event: 2
- Pull request event: 3
- Fork event: 1
- Create event: 3
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| markymarkdaviss | m****4@g****m | 27 |
| jnm703 | b****r@c****m | 26 |
| Robert Reilly | r****7@g****m | 22 |
| Samuel Sharpe | s****e@c****m | 6 |
| danielbarcklow | 1****w | 4 |
| marksibrahim | m****m@g****m | 3 |
| Gil Forsyth | g****h | 2 |
| Ceena Modarres | c****m@C****l | 2 |
| whitesource-bolt-for-github[bot] | 4****] | 1 |
| tmbjmu | 5****u | 1 |
| Santhi S | S****n | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 41
- Total pull requests: 73
- Average time to close issues: 3 months
- Average time to close pull requests: 10 days
- Total issue authors: 9
- Total pull request authors: 14
- Average comments per issue: 0.41
- Average comments per pull request: 0.32
- Merged pull requests: 56
- Bot issues: 26
- Bot pull requests: 12
Past Year
- Issues: 5
- Pull requests: 4
- Average time to close issues: about 1 month
- Average time to close pull requests: 15 minutes
- Issue authors: 1
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 3
- Bot issues: 5
- Bot pull requests: 0
Top Authors
Issue Authors
- mend-bolt-for-github[bot] (12)
- mend-for-github-com[bot] (12)
- rreilly10 (8)
- tazitoo (2)
- markymarkdavis (1)
- cbbruss (1)
- BrunoGomesCoelho (1)
- ashraym (1)
- justin5927 (1)
Pull Request Authors
- rreilly10 (17)
- tazitoo (14)
- mend-for-github-com[bot] (10)
- danielbarcklow (10)
- markymarkdavis (9)
- ashraym (4)
- ssharpe42 (4)
- tmbjmu (2)
- gforsyth (2)
- mend-bolt-for-github[bot] (1)
- hleerighter (1)
- marksibrahim (1)
- ceenam (1)
- dependabot[bot] (1)
Top Labels
Issue Labels
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Packages
- Total packages: 1
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Total downloads:
- pypi 237 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 6
- Total maintainers: 4
pypi.org: gam
Global Explanations for Deep Neural Networks
- Homepage: https://github.com/capitalone/global-attribution-mapping
- Documentation: https://gam.readthedocs.io/
- License: Apache License 2.0
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Latest release: 1.3.0
published over 4 years ago